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<a href="_classifier_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Model for conversion of real valued output to class labels</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> *</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * \author      T. Glasmachers, O.Krause</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * \date        2017</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> *</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> *</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * </span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * </span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * </span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * </span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> *</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> */</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span> </div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="preprocessor">#ifndef SHARK_MODELS_CLASSIFIER_H</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="preprocessor">#define SHARK_MODELS_CLASSIFIER_H</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span> </div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_model_8h.html">shark/Models/AbstractModel.h</a>&gt;</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="comment"></span> </div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="comment">///</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="comment">/// \brief Conversion of real-valued or vector valued outputs to class labels</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="comment">///</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment">/// The Classifier is a model converting the</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="comment">/// real-valued vector output of an underlying decision function to a </span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment">/// class label 0, ..., d-1 by means of an arg-max operation.</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">/// The class returns the argument of the maximal</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment">/// input component as its output. This convertson is adjusted to</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment">/// interpret the output of a linear model, a neural network or a support vector</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">/// machine for multi-category classification.</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">///</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">/// In the special case that d is 1, it is assumed that the model can be represented as</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="comment">/// a 2 d vector with both components having the same value but opposite sign. </span></div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment">/// In consequence, a positive output of the model is interpreted as class 1, a negative as class 0.</span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">///</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">/// The underlying decision function is an arbitrary model. It should</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">/// be default constructable and it can be accessed using decisionFunction().</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">/// The parameters of the Classifier are the ones of the decision function.</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">///</span></div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">/// Optionally the model allows to set bias values which are added on the predicted</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">/// values of the decision function. Thus adding positive weights on a class makes it</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">/// more likely to be predicted. In the binary case with a single output, a positive weight</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment">/// makes class one more likely and a negative weight class 0.</span></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">///</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment">/// \ingroup models</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> Model&gt;</div>
<div class="foldopen" id="foldopen00066" data-start="{" data-end="};">
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html">   66</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_classifier.html" title="Conversion of real-valued or vector valued outputs to class labels.">Classifier</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_model.html" title="Base class for all Models.">AbstractModel</a>&lt;</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>    typename Model::InputType,</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>    unsigned int,</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>    typename Model::ParameterVectorType</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span>&gt;{</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> Model::BatchOutputType ModelBatchOutputType;</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a8ce1b873de955920b900779bf02c719e">   74</a></span>    <span class="keyword">typedef</span> Model <a class="code hl_typedef" href="classshark_1_1_classifier.html#a8ce1b873de955920b900779bf02c719e">DecisionFunctionType</a>;</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a33186c46c8fb9472d9e2c219be2c66f4">   75</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> Model::InputType <a class="code hl_typedef" href="classshark_1_1_classifier.html#a33186c46c8fb9472d9e2c219be2c66f4">InputType</a>;</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a15d0b8ab148d1ea83bee0573213d8f9e">   76</a></span>    <span class="keyword">typedef</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code hl_typedef" href="classshark_1_1_classifier.html#a15d0b8ab148d1ea83bee0573213d8f9e">OutputType</a>;</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#ae56c82feb436eb83115298ba4fd0c89e">   77</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;InputType&gt;::type</a> <a class="code hl_typedef" href="classshark_1_1_classifier.html#ae56c82feb436eb83115298ba4fd0c89e">BatchInputType</a>;</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a997346948fcd63ecfee7be139637c2be">   78</a></span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;unsigned int&gt;::type</a> <a class="code hl_typedef" href="classshark_1_1_classifier.html#a997346948fcd63ecfee7be139637c2be">BatchOutputType</a>;</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a2e36a54e9541fbc7ed0138fd91c9a6a9">   79</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> Model::ParameterVectorType <a class="code hl_typedef" href="classshark_1_1_classifier.html#a2e36a54e9541fbc7ed0138fd91c9a6a9">ParameterVectorType</a>;</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span> </div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#acca41eec396129e8c9859d1115d2bb65">   81</a></span>    <a class="code hl_function" href="classshark_1_1_classifier.html#acca41eec396129e8c9859d1115d2bb65">Classifier</a>(){}</div>
<div class="foldopen" id="foldopen00082" data-start="{" data-end="}">
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a88985a9e17ba8ee00512dbeec74043ad">   82</a></span>    <a class="code hl_function" href="classshark_1_1_classifier.html#a88985a9e17ba8ee00512dbeec74043ad">Classifier</a>(Model <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_classifier.html#adf58b2ed9969bad9828772dd23c59c02" title="Return the decision function.">decisionFunction</a>)</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>    : m_decisionFunction(<a class="code hl_function" href="classshark_1_1_classifier.html#adf58b2ed9969bad9828772dd23c59c02" title="Return the decision function.">decisionFunction</a>){}</div>
</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span> </div>
<div class="foldopen" id="foldopen00085" data-start="{" data-end="}">
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a0badc4c5bfefe6e358c03ca8b115ffdf">   85</a></span>    std::string <a class="code hl_function" href="classshark_1_1_classifier.html#a0badc4c5bfefe6e358c03ca8b115ffdf" title="returns the name of the object">name</a>()<span class="keyword"> const</span></div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <span class="stringliteral">&quot;Classifier&lt;&quot;</span>+m_decisionFunction.name()+<span class="stringliteral">&quot;&gt;&quot;</span>; }</div>
</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    </div>
<div class="foldopen" id="foldopen00088" data-start="{" data-end="}">
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#aaf00d04ae93bc8a05768c6c3055fe79e">   88</a></span>    <a class="code hl_typedef" href="classshark_1_1_classifier.html#a2e36a54e9541fbc7ed0138fd91c9a6a9">ParameterVectorType</a> <a class="code hl_function" href="classshark_1_1_classifier.html#aaf00d04ae93bc8a05768c6c3055fe79e" title="Return the parameter vector.">parameterVector</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>        <span class="keywordflow">return</span> m_decisionFunction.parameterVector();</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>    }</div>
</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span> </div>
<div class="foldopen" id="foldopen00092" data-start="{" data-end="}">
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a0a884c2aea6696bd65f9f195536c05cf">   92</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#a0a884c2aea6696bd65f9f195536c05cf">setParameterVector</a>(<a class="code hl_typedef" href="classshark_1_1_classifier.html#a2e36a54e9541fbc7ed0138fd91c9a6a9">ParameterVectorType</a> <span class="keyword">const</span>&amp; newParameters){</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>        m_decisionFunction.setParameterVector(newParameters);</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>    }</div>
</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span> </div>
<div class="foldopen" id="foldopen00096" data-start="{" data-end="}">
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a6a538027c562c81ca3520173fd0f2802">   96</a></span>    std::size_t <a class="code hl_function" href="classshark_1_1_classifier.html#a6a538027c562c81ca3520173fd0f2802" title="Return the number of parameters.">numberOfParameters</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        <span class="keywordflow">return</span> m_decisionFunction.numberOfParameters();</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>    }</div>
</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>    <span class="comment"></span></div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span><span class="comment">    ///\brief Returns the expected shape of the input</span></div>
<div class="foldopen" id="foldopen00101" data-start="{" data-end="}">
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#ad06d269ebd28e84e9eb9774f10b4c745">  101</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <a class="code hl_function" href="classshark_1_1_classifier.html#ad06d269ebd28e84e9eb9774f10b4c745" title="Returns the expected shape of the input.">inputShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>        <span class="keywordflow">return</span> m_decisionFunction.inputShape();</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span><span class="comment">    ///\brief Returns the shape of the output</span></div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span><span class="comment">    /// For the classifier, Shape is a number representing the number of classes.</span></div>
<div class="foldopen" id="foldopen00107" data-start="{" data-end="}">
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a5a2407d446b736bb6953a467b5dc080d">  107</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_shape.html" title="Represents the Shape of an input or output.">Shape</a> <a class="code hl_function" href="classshark_1_1_classifier.html#a5a2407d446b736bb6953a467b5dc080d" title="Returns the shape of the output.">outputShape</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>        <span class="keywordflow">return</span> m_decisionFunction.outputShape().flatten();</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>    }</div>
</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>    </div>
<div class="foldopen" id="foldopen00111" data-start="{" data-end="}">
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">  111</a></span>    RealVector <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">bias</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>        <span class="keywordflow">return</span> m_bias;</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>    }</div>
</div>
<div class="foldopen" id="foldopen00114" data-start="{" data-end="}">
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a9742c8125eb03f0e40281945dd98de46">  114</a></span>    RealVector&amp; <a class="code hl_function" href="classshark_1_1_classifier.html#a9742c8125eb03f0e40281945dd98de46">bias</a>(){</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        <span class="keywordflow">return</span> m_bias;</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>    }</div>
</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>    <span class="comment"></span></div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span><span class="comment">    /// \brief Return the decision function</span></div>
<div class="foldopen" id="foldopen00119" data-start="{" data-end="}">
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#adf58b2ed9969bad9828772dd23c59c02">  119</a></span><span class="comment"></span>    Model <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_classifier.html#adf58b2ed9969bad9828772dd23c59c02" title="Return the decision function.">decisionFunction</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>        <span class="keywordflow">return</span> m_decisionFunction;</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>    }</div>
</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>    <span class="comment"></span></div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span><span class="comment">    /// \brief Return the decision function</span></div>
<div class="foldopen" id="foldopen00124" data-start="{" data-end="}">
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#af29209184ee464261cc9b668d71ba6e1">  124</a></span><span class="comment"></span>    Model&amp; <a class="code hl_function" href="classshark_1_1_classifier.html#af29209184ee464261cc9b668d71ba6e1" title="Return the decision function.">decisionFunction</a>(){</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>        <span class="keywordflow">return</span> m_decisionFunction;</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>    }</div>
</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>    </div>
<div class="foldopen" id="foldopen00128" data-start="{" data-end="}">
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#aa0fe007fbef4ec06e2a67ddf844f889d">  128</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#aa0fe007fbef4ec06e2a67ddf844f889d">eval</a>(<a class="code hl_typedef" href="classshark_1_1_classifier.html#ae56c82feb436eb83115298ba4fd0c89e">BatchInputType</a> <span class="keyword">const</span>&amp; input, <a class="code hl_typedef" href="classshark_1_1_classifier.html#a997346948fcd63ecfee7be139637c2be">BatchOutputType</a>&amp; output)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(m_bias.empty() || m_decisionFunction.outputShape().numElements() == m_bias.size());</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>        ModelBatchOutputType modelResult;</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>        m_decisionFunction.eval(input,modelResult);</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>        std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = modelResult.size1();</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>        output.resize(<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>        <span class="keywordflow">if</span>(modelResult.size2()== 1){</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>            <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">bias</a> = m_bias.empty()? 0.0 : m_bias(0);</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span>            <span class="keywordflow">for</span>(std::size_t i = 0; i != <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>; ++i){</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span>                output(i) = modelResult(i,0) + <a class="code hl_function" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">bias</a> &gt; 0.0;</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>            }</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>        }</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>            <span class="keywordflow">for</span>(std::size_t i = 0; i != <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>; ++i){</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>                <span class="keywordflow">if</span>(m_bias.empty())</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>                    output(i) = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(arg_max(row(modelResult,i)));</div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>                <span class="keywordflow">else</span></div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>                    output(i) = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(arg_max(row(modelResult,i) + m_bias));</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span>            }</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>        }</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>    }</div>
</div>
<div class="foldopen" id="foldopen00149" data-start="{" data-end="}">
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a06babaf2a8d4022a2727f5654c9e9237">  149</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#a06babaf2a8d4022a2727f5654c9e9237">eval</a>(<a class="code hl_typedef" href="classshark_1_1_classifier.html#ae56c82feb436eb83115298ba4fd0c89e">BatchInputType</a> <span class="keyword">const</span>&amp; input, <a class="code hl_typedef" href="classshark_1_1_classifier.html#a997346948fcd63ecfee7be139637c2be">BatchOutputType</a>&amp; output, <a class="code hl_struct" href="structshark_1_1_state.html" title="Represents the State of an Object.">State</a>&amp; state)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>        <a class="code hl_function" href="classshark_1_1_classifier.html#aa0fe007fbef4ec06e2a67ddf844f889d">eval</a>(input,output);</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>    }</div>
</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>    </div>
<div class="foldopen" id="foldopen00153" data-start="{" data-end="}">
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a6efcef45c2cecbf50e2021dc1fab842c">  153</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#a6efcef45c2cecbf50e2021dc1fab842c" title="Standard interface for evaluating the response of the model to a single pattern.">eval</a>(<a class="code hl_typedef" href="classshark_1_1_classifier.html#a33186c46c8fb9472d9e2c219be2c66f4">InputType</a> <span class="keyword">const</span> &amp; pattern, <a class="code hl_typedef" href="classshark_1_1_classifier.html#a15d0b8ab148d1ea83bee0573213d8f9e">OutputType</a>&amp; output)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(m_bias.empty() || m_decisionFunction.outputShape().numElements() == m_bias.size());</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>        <span class="keyword">typename</span> Model::OutputType modelResult;</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>        m_decisionFunction.eval(pattern,modelResult);</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>        <span class="keywordflow">if</span>(m_bias.empty()){</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>            <span class="keywordflow">if</span>(modelResult.size() == 1){</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>                <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">bias</a> = m_bias.empty()? 0.0 : m_bias(0);</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>                output = modelResult(0) + <a class="code hl_function" href="classshark_1_1_classifier.html#ae97fca135ea08ed2c8e60d01b3aad117">bias</a> &gt; 0.0;</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>            }</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>            <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>                <span class="keywordflow">if</span>(m_bias.empty())</div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span>                    output = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(arg_max(modelResult));</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>                <span class="keywordflow">else</span></div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>                    output = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(arg_max(modelResult + m_bias));</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span>            }</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>        }</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>    }</div>
</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>    <span class="comment"></span></div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span><span class="comment">    /// From ISerializable</span></div>
<div class="foldopen" id="foldopen00172" data-start="{" data-end="}">
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#acb5a2d1e5b06c0ef549b3e55d495cdc7">  172</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#acb5a2d1e5b06c0ef549b3e55d495cdc7" title="From ISerializable.">read</a>(<a class="code hl_typedef" href="namespaceshark.html#ada68729491840669e47c8ad42282424f" title="Type of an archive to read from.">InArchive</a>&amp; archive){</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>        archive &gt;&gt; m_decisionFunction;</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>        archive &gt;&gt; m_bias;</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span><span class="comment">    /// From ISerializable</span></div>
<div class="foldopen" id="foldopen00177" data-start="{" data-end="}">
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno"><a class="line" href="classshark_1_1_classifier.html#a580c095f6fdbb8abb438ad7af392bc77">  177</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_classifier.html#a580c095f6fdbb8abb438ad7af392bc77" title="From ISerializable.">write</a>(<a class="code hl_typedef" href="namespaceshark.html#af4f8eb8e9618f5236b71bbcb12b8a524" title="Type of an archive to write to.">OutArchive</a>&amp; archive)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>        archive &lt;&lt; m_decisionFunction;</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>        archive &lt;&lt; m_bias;</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>    }</div>
</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>    </div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>    Model m_decisionFunction;</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>    RealVector m_bias;</div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>};</div>
</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span> </div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>};</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span><span class="preprocessor">#endif</span></div>
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